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Sentiment analysis using automatic classification on online media article

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The increasing demand for an automatic sentiment measurement is becoming critical in this era. Therefore, this topic is becoming one of the most encountered reseraches in data mining and NLP. Sentiment analysis is a process of classifying articles as a positive or negative. This kind of approach is lacking of multiple assessor?s valuation. In order to do so, a more humanly semantic classification is needed. There are various researches on developing an algorithm for sentiment analysis by using classification, such as research by Turney (2010) and Pang (2008). The main purpose of this research is to design and implement a system that can analyze sentiment of text in Bahasa Indonesia. The article will be categorized into one of two sentiments: positive or negative. The text is an online digital media streaming article. Sentiment analysis will use automatic classification to analyze the sentiment.

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Availability

B01364

(wh)

Available

Detail Information

Series Title

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Call Number

1364

Publisher

: Swiss German University., 2013

Collation

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Language

English

ISBN/ISSN

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Classification

NONE

Content Type

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Media Type

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Carrier Type

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Edition

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Subject(s)

IT

Specific Detail Info

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Statement of Responsibility

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